Scaling up quantum chemistry simulations using density matrix embedding theory

Presenting Author: Yukio Kawashima, 1QB Information Technologies

The simulation of large molecules using quantum computing is promising. The computational resources required scale only polynomially against molecular size, but do so exponentially when using classical computers. Quantum computing remains limited in computational resources, so computational costs must be reduced. Problem decomposition (PD) techniques are powerful tools able to reduce computational costs in maintaining accuracy in quantum chemistry simulations. The application of PD techniques shows promise in helping to scale up the ability to simulate larger molecules. We have developed QEMIST (Quantum-Enabled Molecular ab Initio Simulation Toolkit), a platform for both the classical and quantum simulation of large molecules, employing PD techniques. One PD technique implemented in QEMIST is the density matrix embedding theory (DMET). Its use involves decomposing a molecule into fragments, each fragment treated as an open quantum system entangled with each other fragment, all taken together to constitute a fragment's surrounding environment. We created an interface using DMET and quantum algorithms to perform quantum chemistry simulations. DMET-based simulation on a ring of 10 hydrogen atoms reduced the required number of qubits from 20 to 4; the error of calculated molecular energy was within 1.0 kcal/mol compared to the exact value. Employing the DMET method improved our ability to simulate larger molecules than conventional simulation techniques not making use of PD.

(Session 9a : Sunday from 4:45pm - 5:15pm)


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Postdoctoral Fellows:
Markus Allgaier (UO OMQ)
Sayonee Ray (UNM CQuIC)
Pablo Poggi (UNM CQuIC)
Valerian Thiel (UO OMQ)

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Holly Lynn

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